Unable to sample conditionally in Tabular_Preset model

[bhaveshneekhra]

Environment Details

Please indicate the following details about the environment in which you found the bug:

• SDV version: 0.14.1
• Python version: 3.8.10
• Operating System: Ubuntu 20.04.3

Error Description

I am just reproducing this code at https://sdv.dev/SDV/user_guides/single_table/tabular_preset.html#conditional-sampling.

Steps to reproduce

Just run everything on the page till https://sdv.dev/SDV/user_guides/single_table/tabular_preset.html#conditional-sampling

If there was a crash, please include the traceback here.

---

TypeError Traceback (most recent call last)
in
----> 1 model.sample_conditions(conditions = all_conditions)

~/.local/lib/python3.8/site-packages/sdv/lite/tabular.py in sample_conditions(self, conditions, max_tries, batch_size_per_try, randomize_samples, output_file_path)
196 Sampled data.
197 """
--> 198 sampled = self._model.sample_conditions(
199 conditions, max_tries, batch_size_per_try, randomize_samples, output_file_path)
200

TypeError: sample_conditions() takes from 2 to 5 positional arguments but 6 were given

[npatki]

Hi @bhaveshneekhra -- thanks for filing. We'll look into this.

Did you also follow the step to save and reload the model? I observed that it works fine if you do this, but it crashes if you skip this part.

I'd suggest saving and re-loading as a temporary workaround.

model.save('fast_ml_model.pkl')
model = TabularPreset.load('fast_ml_model.pkl')

conditioned_data = model.sample_conditions(conditions=all_conditions)